Fao Semantics Related Projects


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  • Fao Semantics Related Projects

    1. 1. Semantic Technologies at FAO Bioversity International, Maccarese, Roma, Italy Margherita Sini 20 April 2009
    2. 2. Few words about myself
    3. 3. Just a very rapid introduction <ul><li>What? </li></ul><ul><ul><li>semantic, semantic web, semantic technologies </li></ul></ul><ul><ul><li>ontologies, Knowledge Organization Systems, </li></ul></ul><ul><ul><li>metadata </li></ul></ul><ul><li>Why? </li></ul><ul><ul><li>interoperability, exchange, share </li></ul></ul><ul><ul><li>user orientation, precision and recall </li></ul></ul><ul><ul><li>multilinguality, cultural views, context </li></ul></ul><ul><li>Who? </li></ul><ul><ul><li>everybody, all domains, all countries, all .org </li></ul></ul><ul><li>Which instruments? </li></ul><ul><ul><li>experts, NLP, methodologies and techniques </li></ul></ul>
    4. 4. Outline <ul><li>Semantic projects involving FAO </li></ul><ul><ul><li>AOS </li></ul></ul><ul><ul><li>IPFSAPH, FNA, CWR, Fisheries, Food & nutrition, Geopolitical ontology, AGROVOC Concept Server </li></ul></ul><ul><ul><li>Thai Rice Onto, Agropedia Indica </li></ul></ul><ul><li>Methods and Methodologies </li></ul><ul><ul><li>Ontology models (AGROVOC Concept Server, LIR, ...) </li></ul></ul><ul><ul><li>Modeling considerations </li></ul></ul><ul><li>What’s next </li></ul><ul><ul><li>networked ontologies </li></ul></ul><ul><ul><li>ontology-based applications </li></ul></ul><ul><ul><li>collaborations </li></ul></ul>
    5. 5. Semantic projects involving FAO
    6. 6. Why AOS vessel? craft? boat? bateaux? barco? Terminology brokering Semantic navigation, Clustering, Ranking, ... Intelligent query expansion Interoperability Inferencing Reasoning Machine learning ship or container
    7. 7. Agricultural Ontology Service <ul><li>an FAO initiative for more coherence in Agricultural Information Systems </li></ul><ul><li>multiple partners </li></ul><ul><li>need of a semantic approach </li></ul><ul><li>AOS elements: </li></ul><ul><ul><li>AGROVOC Concept Server </li></ul></ul><ul><ul><li>KOS registry </li></ul></ul><ul><ul><li>Mapping registries </li></ul></ul><ul><ul><li>Metadata standards </li></ul></ul><ul><ul><li>Tools (refinement tool, WB, ...) </li></ul></ul><ul><li>Built from AGROVOC </li></ul><ul><li>Domain concepts </li></ul><ul><li>Categories </li></ul>AGROVOC Concept Server Ontology registry Sub-domain ontologies Metadata ontologies
    8. 8. IPFSAPH
    9. 9. IPFSAPH
    10. 10. The Ontology
    11. 11. Creation of the core ontology 1600 concepts 3 languages <ul><li>Information Resources </li></ul><ul><li>Brainstorming </li></ul><ul><li>Codex Alimentarius </li></ul><ul><li>SPS Agreement </li></ul>Ontology subject specialists AGROVOC Food Safety Documents Generic Documents Ontology Editor (OI-Modeler)
    12. 12. Features: Concept Search The same records will be retrieved regardless of the specific synonyms or singular/plural forms that the user uses to refer to a concept. Related concepts
    13. 13. Features: Multilinguality The system is also able to understand a concept even when different languages are used.
    14. 14. Features: Check spelling Spelling errors are corrected: e.g. “desease” into “disease”
    15. 15. Features: Paraphrasing “ mad cow disease symptoms” or “clinical signs of bovine spongiform encephalopathy”
    16. 16. give the same results, which are ranked.
    17. 17. Features: Semantic Navigation of Knowledge parent concept(s) children concept(s)
    18. 18. FNA
    19. 19. FNA
    21. 21. The ontology concepts <ul><li>Publication </li></ul><ul><li>Issue </li></ul><ul><li>Work </li></ul><ul><ul><li>Article </li></ul></ul><ul><li>Subject Term </li></ul><ul><li>Category </li></ul><ul><li>Author </li></ul><ul><li>Region </li></ul><ul><li>Language </li></ul><ul><li>Year </li></ul>
    22. 22. Ontology Relationships
    23. 23. The ontology instances
    24. 24. Features <ul><li>Multilingual concept resolution </li></ul><ul><li>Get suggestions for the navigation (e.g. synonyms) </li></ul><ul><li>Guided query formulation </li></ul><ul><li>Easy navigation of the objects by following the semantic links </li></ul>
    25. 25. RDFa
    26. 26. Features (cont.)
    27. 27. CWR
    28. 28. The project <ul><li>International partners (BGCI, Bioversity International, BLE, FAO, IUCN, UNEP WCMC) </li></ul><ul><li>Developed in harmony with CWR descriptor list </li></ul><ul><li>First version (English only) available by December 2006 </li></ul><ul><li>About 800 core terms + acronyms + spelling variants </li></ul><ul><li>Clearly definition of concepts (AGROVOC + other sources) </li></ul><ul><li>Relationships: hierarchical + causative </li></ul>
    29. 29. The Ontology <ul><li>OWL Full </li></ul><ul><li>http://www.fao.org/aims/aos/cwr.owl </li></ul>
    30. 30. More semantics Term: wild plants subclass of plants superclass of crop wild relatives adapted by domestication benefits from resource conservation
    31. 31. Ontology properties (1/2)
    32. 32. Ontology properties (2/2)
    33. 33. Fisheries
    34. 34. The project OneFish FIGIS AGROVOC Aquaculture Resource Water Area land strains Species life cycle Farming system management system Production center Spawning technique Breeding technique Hatchery technique Expl. form Regulation Farming technique Environment Institution Health monitoring technique diseases suppliers ASFA
    35. 35. Basic activities in FOS Catalog building PRECEDES PRECEDES PRECEDES Ontology Merging Wrapping Terminology Re-engineering Formatting Union Mapping Interfacing Exploitation Matching Discovery Consistency checking Formalization Conceptual Integration Analysis Importing Descriptors Terms Relations Scope notes Subjects Identifiers Codes DB specific links Concepts Relations Axioms Rules Lexicalization Annotations @ CNR
    36. 36. Foundational Ontology FOS core FOS integrated FOS merged FIGIS Reference Tables ASFA FIGIS DTD ONE FISH AGROVOC
    37. 37. The Ontology
    38. 38. Features <ul><li>Form versus meaning: </li></ul><ul><ul><li>Traditional Search </li></ul></ul><ul><ul><li>Concept Search </li></ul></ul><ul><li>Implemented functionalities: </li></ul><ul><ul><li>synonym search </li></ul></ul><ul><ul><li>multilingual capability </li></ul></ul><ul><ul><li>terminology brokering </li></ul></ul><ul><ul><li>disambiguation </li></ul></ul><ul><ul><li>related concepts </li></ul></ul><ul><ul><li>query expansion </li></ul></ul><ul><li>Basic natural language queries </li></ul><ul><li>Semantic navigation of bibliographical metadata </li></ul><ul><li>Semantic Navigation of Knowledge </li></ul><ul><ul><li>Alphabetic list ... </li></ul></ul><ul><ul><li>Core Fishery Concepts ... </li></ul></ul>
    39. 39. Ontology properties
    40. 40. Example <ul><li>&quot;tell me what vessels from a nearby country are currently in the marine area 50N060W within Atlantic Ocean, provided that also some Thunnus alalunga stock can be fished by those vessels, through allowed techniques&quot; </li></ul>
    41. 41. Using multilingual lexicalizations ENGLISH SPANISH FRENCH
    42. 42. Using hierarchically related concepts hierarchically related concept Polyvalent Trawlers
    43. 43. Using non-hierarchically related concepts non-hierarchically related concept gears
    44. 44. Help the user formulate queries Original query: bateau de pêche To refine your query, click on the concepts you are interested in. They will appear to the left. Search:
    45. 45. Reconcile different vocabularies “ navire de p ê che”, “fishing vessel”, “ embarcaciones de pesca” AGROVOC or ASFA or other “ fishing vessels,” “ fishing boat,” AGROVOC: “fishing vessels”, “barco”, etc... ASFA: “fishing vessels”
    46. 46. Semantic Navigation of Knowledge: Thesaurus based Highlighting the originator thesaurus. User can select a specific thesaurus to look for.
    47. 48. Geopolitical ontology
    48. 49. Geopolitical ontology <ul><li>Incorporate geopolitical data </li></ul><ul><li>Will serve as a bridge to allow communication between the various systems </li></ul>
    49. 50. Properties <ul><li>isValidFrom </li></ul><ul><li>hasOfficialName </li></ul><ul><li>hasCode </li></ul><ul><li>isSuccessorOf </li></ul><ul><li>hasBorderWith </li></ul><ul><li>dependsOn </li></ul>
    50. 51. Nutrition Ontology
    51. 53. Procedure =CONCATENATE(&quot;<owl:Class rdf:ID=&quot;&quot;&quot;,J2,&quot;&quot;&quot;><rdfs:subClassOf><owl:Class rdf:ID=&quot;&quot;c_&quot;,B2,&quot;&quot;&quot;/></rdfs:subClassOf><rdfs:label xml:lang=&quot;&quot;en&quot;&quot;><![CDATA[&quot;,D2,&quot;]]></rdfs:label><code><![CDATA[&quot;,J2,&quot;]]></code><TAGNAME><![CDATA[&quot;,J2,&quot;]]></TAGNAME>&quot;,S2, T2,&quot;</owl:Class>&quot;) <?xml version=&quot;1.0&quot;?> <rdf:RDF xmlns=&quot;http://www.fao.org/aos/infoods#&quot; xmlns:protege=&quot;http://protege.stanford.edu/plugins/owl/protege#&quot; xmlns:rdf=&quot;http://www.w3.org/1999/02/22-rdf-syntax-ns#&quot; xmlns:xsd=&quot;http://www.w3.org/2001/XMLSchema#&quot; xmlns:rdfs=&quot;http://www.w3.org/2000/01/rdf-schema#&quot; xmlns:owl=&quot;http://www.w3.org/2002/07/owl#&quot; xmlns:daml=&quot;http://www.daml.org/2001/03/daml+oil#&quot; xmlns:dc=&quot;http://purl.org/dc/elements/1.1/&quot; xml:base=&quot;http://www.fao.org/aos/infoods&quot;> <owl:Ontology rdf:about=&quot;&quot;> <owl:imports rdf:resource=&quot;http://protege.stanford.edu/plugins/owl/protege&quot;/> <owl:versionInfo rdf:datatype=&quot;http://www.w3.org/2001/XMLSchema#string&quot; >Revision 4.0</owl:versionInfo> <protege:defaultLanguage rdf:datatype=&quot;http://www.w3.org/2001/XMLSchema#string&quot; >en</protege:defaultLanguage> <rdfs:comment rdf:datatype=&quot;http://www.w3.org/2001/XMLSchema#string&quot; >International Network of Food Data Systems (INFOODS) was established in 1984 on the basis of the recommendations of an international group convened under the auspices of the United Nations University (UNU). Its goal was to .....</rdfs:comment> </owl:Ontology> <owl:Class rdf:ID=&quot;c_0413&quot;> <code rdf:datatype=&quot;http://www.w3.org/2001/XMLSchema#string&quot; >0413</code> <rdfs:subClassOf> <owl:Class rdf:ID=&quot;c_041&quot;/> </rdfs:subClassOf> <rdfs:label xml:lang=&quot;en&quot;>Vitamin D</rdfs:label> </owl:Class>
    52. 54. AGROVOC
    53. 55. AOS Core: the Concept Server Export mapping Terminology Workbench AGROVOC OWL AGROVOC RDFS formats (e.g. SKOS) and TagText ISO2709 Other thesauri and terminologies integration ABACA NT1 Food NT2 Apple ANIMAL BT Organ NT .... Other thesauri & terminologies ABACA NT1 Food NT2 Apple ANIMAL BT Organ NT ....
    54. 56. Concept Server project <ul><li>Refine semantics and enrich data pool and lexicon </li></ul><ul><li>Develop a workbench for terminology and ontology development and maintenance </li></ul><ul><li>Support information management specialists in the development, maintenance, and quality assurance of the AGROVOC CS </li></ul><ul><li>Global knowledge vs Local knowledge </li></ul>
    55. 57. AGROVOC Concept Server <ul><li>AGROVOC cleaning and refinement </li></ul>Current AGROVOC MySQL Improved AGROVOC MySQL AGROVOC OWL Revision and Refinement
    56. 58. Modeling <ul><li>Conversion to UTF-8 </li></ul><ul><li>Incorporated AGRIS/CARIS classification scheme (multilingual) and the mapping with AGROVOC keywords </li></ul><ul><li>Modified structure to store multiple classification schemes </li></ul><ul><li>Export to OWL format (v0.8a) </li></ul><ul><li>Export to SKOS format (v0.8a) </li></ul><ul><li>Revised RDBMS scheme for ontology representation </li></ul><ul><li>Identified the ontological model + represent in OWL </li></ul>
    57. 59. Thai Rice Ontology
    58. 60. Thai Rice Onto metadata repository
    59. 61. Plant ontology: Relationship types Taxon <hasSuperclass> Taxon Taxon <has GrowthType> GrowthType Taxon <hasPropagationMethod> PropagationMethod Taxon <occursIn> Environment Taxon <hasPest> Taxon Taxon <hasDisease> Disease Disease <causedBy> Taxon TaxonPart <isa> AnatomicalPart TaxonPart <isa> AnatomicalTypeOfFruit TaxonPart <partOf> Taxon TaxonPart <usedAs> Use TaxonPart <usedToMake> ProductType Taxon <hasDescription> Text
    60. 62. Thai plant ontology: Example Mangifera indica Linn. <hasSuperclass> Mangifera Mangifera indica Linn. <hasGrowthType> tree Mangifera indica Linn. <hasPropagationMethod> seedling Mangifera indica Linn <hasDescription> &quot;leaves ...., flower ...... “ Mangifera indica Linn <occursIn> dry soil Mangifera indica Linn. <hasPest> Scirtothrips dosalis Hood Mangifera indica Linn <hasPest> Oidium mangiferae OR, instead of the last statement or in addition to it Mangifera indica Linn <hasDisease> Powdery Mildew Powdery mildew <caused by> Oidium mangiferae
    61. 63. Agropedia Indica
    62. 64. Agropedia Indica <ul><li>http://www.slideshare.net/marghe_rita/1-pantnagar </li></ul><ul><li>http://www.slideshare.net/marghe_rita/2-pantnagar-w-guidelines </li></ul><ul><li>http://www.slideshare.net/marghe_rita/3-pantnagar-w-exercices </li></ul><ul><li>http:// agropedia.iitk.ac.in / </li></ul><ul><li>Guidelines </li></ul>
    63. 65. Retrieval Navigate KM JAVA+ JENA results..... this is a document about rice and its pests..... Once the rice ap- pear in the world ..... Mad Cow Disea- se is the commonly used name for Bovine Spongiform Encephalopathy (BSE) ....
    64. 66. And also...
    65. 67. Other projects <ul><li>Language ontology </li></ul><ul><ul><li>http://www.fao.org/aims/aos/languagecode.owl </li></ul></ul><ul><li>AGRIS metadata ontology </li></ul><ul><li>... </li></ul>
    66. 68. Ontology Construction Methodologies / Methods
    67. 69. Several points to consider <ul><li>Start from existing KOS </li></ul><ul><li>Incorporate Terminology/Concepts from sources </li></ul><ul><li>Different data models to homogenize / link / merge </li></ul><ul><li>From RDBMS/excel to RDFS/OWL </li></ul><ul><li>Make use of existing standards (Dublin Core) </li></ul><ul><li>From unstructured data to formalized data </li></ul><ul><li>Available tools </li></ul>
    68. 70. Modeling <ul><li>Identify use cases / Application needs </li></ul><ul><li>Competency questions </li></ul><ul><li>Identify the ontological model + Evaluate standards </li></ul><ul><ul><li>AGROVOC </li></ul></ul><ul><ul><li>NeOn LIR </li></ul></ul><ul><ul><li>Others </li></ul></ul><ul><li>Identify tools / APIs </li></ul><ul><ul><li>Performances! </li></ul></ul><ul><ul><li>Development team! </li></ul></ul><ul><ul><li>Maintenance team (domain experts)! </li></ul></ul><ul><li>Process </li></ul><ul><ul><li>Conversion to UTF-8 </li></ul></ul><ul><ul><li>Merging schemes / data </li></ul></ul><ul><ul><li>Automatic tools  expert revision! </li></ul></ul><ul><li>Guidelines </li></ul>
    69. 71. Ontology models: AGROVOC Concept Relationships between concepts Lexicalization/ Term String Relationships between strings Relationships between terms designated by manifested as Other information: language/culture subvocabulary/scope audience type, etc. Note annotation relationship Relationship Relationships between Relationships All terms are created as instances of the class o_terms. All at the same level. Only one language per term. term level string level concept level
    70. 72. LIR
    71. 73. Modeling (cont.) <ul><li>concepts from descriptors </li></ul><ul><li>Synonym <owl:DatatypeProperty rdf:ID=&quot;synonym&quot;> </li></ul><ul><li>Acronyms <owl:AnnotationProperty rdf:about=&quot;http://www.fao.org/aos/agrovoc/2005#acronym&quot;> </li></ul><owl:Class rdf:about=&quot; http://www.fao.org/aos/agrovoc/2005 #c_3&quot;> <rdfs:label xml:lang=&quot;en&quot;>ABA</rdfs:label> <rdfs:label xml:lang=&quot;fr&quot;>ABA</rdfs:label> <rdfs:label xml:lang=&quot;es&quot;>ABA</rdfs:label> <rdfs:label xml:lang=&quot;ar&quot;>آبا</rdfs:label> <rdfs:label xml:lang=&quot;zh&quot;>脱落酸</rdfs:label> <synonym xml:lang=&quot;en&quot;>[8565] Abscisic acid</synonym> <rdfs:subClassOf rdf:resource=&quot; http://www.fao.org/aos/agrovoc/2005 #c_3397&quot;/> <rdfs:subClassOf rdf:resource=&quot; http://www.fao.org/aos/agrovoc/2005 #c_32543&quot;/> </owl:Class>
    72. 74. Modeling (cont.): Registries concepts, relationships Y <pest> X. An organism Y can be harmed by organism X. E.g. &quot;Litchi chinensis&quot; <pest> &quot;Bactrocera dorsalis&quot;; <pest> pest X <pest_of> Y. An organism X causes harm to organism Y. E.g. &quot;Bactrocera dorsalis&quot; <pest_of> &quot;Litchi chinensis&quot;; <pest_of> pest of Y <is_use_of> X. For use within the plant domain, {Use} <is_use_of> {Taxon},. and for chemical substances {use} <is_use_of> {chemical substance}. E.g.: &quot;fruit&quot; <is_use_of> &quot;apple&quot;; &quot;cleaner&quot; <is_use_of> &quot;alcohol&quot;; &quot;pesticide&quot; <is_use_of> &quot;ddt&quot;; <is_use_of> is use of X <used_as> Y. Thus far, restricted to plant domain, i.e., {Taxon} <used_as> {use}, and for uses of chemicals i.e., {chemical substance} <used_as> {use}. E.g.: &quot;apple&quot; <used_as> &quot;fruit&quot;; &quot;alcohol&quot; <used_as> &quot;cleaner&quot;; &quot;ddt&quot; <used_as> &quot;pesticide&quot;. <used_as used as X <part> Y. A composite entity X that can be identified as having one or more parts Y. Use this relationship when none of the other partitivity relations (<component>, <composed_of>, <portion>, <member>, <includes_subprocess>) apply. part part Y <part_of> X. Part Y is a constituent of entity X. Use this relationship when none of the other partitivity relations (<component>, <composed_of>, <portion>, <member>, <includes_subprocess>) apply. E.g. in a plant ontology: {PlantPart} <part_of> {taxon} partOf part of X <superclass_of> Y. X is more general than Y in the sense that X is characterized by having a subset of the features of Y. E.g. { milk } <superclass_of> { cow's milk }. superclassOf superclass of Y <subclass_of> X. Y has all the features of X plus additional ones which make it more specific than X. E.g. { cow's milk } <subclass_of> { milk }. subclassOf subclass of
    73. 75. What’s next
    74. 76. Networked ontologies: AOS Market [email_address] general Pest [email_address] Application Specific Layer Other Specific Ontologies Domain Specific Layer Agricultural Domain Specific Ontologies (may) import (may) import same URI Rice [email_address] Rice [email_address] general Pest [email_address] Plant [email_address] Rice [email_address] Indian Rice [email_address] Indian Rice Cultivation [email_address] Pest activity [email_address]
    75. 77. Ontology-based applications <ul><li>Better exploitation of the potentiality at the application level: powerful IR, reasoning </li></ul><ul><li>No more words but URIs in IS </li></ul><ul><li>Ontology Web services (OWS) </li></ul>
    76. 78. Ontology-based Application Search for: Search for: Providers Metadata Layer Ontology Layer Web Interface Search for: ok Stemming Disambiguation Check-spelling ... concepts resolution < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> < dc:title /> < /> < /> < /> < /> <OWL .....> </OWL> dc:title dc:subject dc:author <OWL .....> </OWL> rights gmo
    77. 79. Future AOS Ontologies Grid internet Networked CS ontologies Health Modules CS Modules AGROVOC CS Workbench HEALTH CS Workbench My Personal CS Workbench My Personal CS Workbench My Personal CS Workbench .... organisms substances .... health medicine Thai Agriculture Ontology CS Workbench .... rice corn para rubber sugarcane .... rice mango sorghum IITK Modules Agropedia Indica Workbench
    78. 80. Collaborations <ul><li>With AOS partners </li></ul><ul><li>Mapping projects </li></ul><ul><li>NeOn </li></ul><ul><li>SEMIC.EU </li></ul><ul><li>GBIF Global Biodiversity Information Facility secretariat </li></ul><ul><li>JRC + BGS </li></ul><ul><li>Ecoterm </li></ul>
    79. 81. Take-home message <ul><li>There are many uses for terminology + ontology systems in food and agriculture, both for information access and information processing </li></ul><ul><li>FAO has several projects using such systems </li></ul><ul><li>FAO and partners are deploying the Agricultural Ontology Server (AOS) as a global resource </li></ul>
    80. 82. Questions? Thanks Margherita Sini: margherita.Sini@fao.org Johannes Keizer: Johannes.Keizer@fao.org Dagobert Soergel: dsoergel@umd.edu Asanee Kawtrakul: [email_address] But Also: Gudrun Johannsen, Boris Lauser, Claudio Baldassarre, Gauri Salokhe, Marta Iglesias, Caterina Caracciolo, Sachit Rajbhandari, Jeetendra Singh, Mary Redahan, Shrestha, Prashanta, Ton, Imm, Thanapth, Trakul, and many others...